Association between neighborhood socioeconomic status, built environment and SARS‐CoV‐2 infection among cancer patients treated at a Tertiary Cancer Center in New York City

Abstract Background Racial and ethnic minority groups experience a disproportionate burden of SARS‐CoV‐2 illness and studies suggest that cancer patients are at a particular risk for severe SARS‐CoV‐2 infection. Aims The objective of this study was examine the association between neighborhood characteristics and SARS‐CoV‐2 infection among patients with cancer. Methods and Results We performed a cross‐sectional study of New York City residents receiving treatment for cancer at a tertiary cancer center. Patients were linked by their address to data from the US Census Bureau's American Community Survey and to real estate tax data from New York's Department of City Planning. Models were used to both to estimate odds ratios (ORs) per unit increase and to predict probabilities (and 95% CI) of SARS‐CoV2 infection. We identified 2350 New York City residents with cancer receiving treatment. Overall, 214 (9.1%) were infected with SARS‐CoV‐2. In adjusted models, the percentage of Hispanic/Latino population (aOR = 1.01; 95% CI, 1.005–1.02), unemployment rate (aOR = 1.10; 95% CI, 1.05–1.16), poverty rates (aOR = 1.02; 95% CI, 1.0002–1.03), rate of >1 person per room (aOR = 1.04; 95% CI, 1.01–1.07), average household size (aOR = 1.79; 95% CI, 1.23–2.59) and population density (aOR = 1.86; 95% CI, 1.27–2.72) were associated with SARS‐CoV‐2 infection. Conclusion Among cancer patients in New York City receiving anti‐cancer therapy, SARS‐CoV‐2 infection was associated with neighborhood‐ and building‐level markers of larger household membership, household crowding, and low socioeconomic status. Novelty and impact We performed a cross‐sectional analysis of residents of New York City receiving treatment for cancer in which we linked subjects to census and real estate date. This linkage is a novel way to examine the neighborhood characteristics that influence SARS‐COV‐2 infection. We found that among patients receiving anti‐cancer therapy, SARS‐CoV‐2 infection was associated with building and neighborhood‐level markers of household crowding, larger household membership, and low socioeconomic status. With ongoing surges of SARS‐CoV‐2 infections, these data may help in the development of interventions to decrease the morbidity and mortality associated with SARS‐CoV‐2 among cancer patients.

characteristics that influence SARS-COV-2 infection. We found that among patients receiving anti-cancer therapy, SARS-CoV-2 infection was associated with building and neighborhood-level markers of household crowding, larger household membership, and low socioeconomic status. With ongoing surges of SARS-CoV-2 infections, these data may help in the development of interventions to decrease the morbidity and mortality associated with SARS-CoV-2 among cancer patients.

| INTRODUCTION
Racial and ethnic minority groups experience a disproportionate burden of SARS-CoV-2 illness. 1,2 In New York City, the incidence of COVID-19 varies substantially based on area of residence and is higher in neighborhoods traditionally characterized by lower socioeconomic status. 3,4 Additionally, there were two significant outbreaks (March-May and December) of COVID-19 in 2020 in New York City. 5 Previous studies suggest that cancer patients are at a particular risk for severe SARS-CoV-2 infection. 6 Our objective was to determine the interplay of race and neighborhood socioeconomic factors on SARS-CoV-2 infection among oncology patients during a period of wide community spread of the virus.

| METHODS
We performed a cross-sectional study of residents of New York City receiving treatment for cancer at a tertiary cancer center from March 1, 2020 to December 31, 2020. Patients were identified by ICD-10 cancer diagnosis codes in combination with billing codes for chemotherapy, targeted therapy or radiotherapy. SARS-CoV-2 status was determined by review of SARS-CoV-2 test results or documentation of infection from the medical record. Any SARS-CoV-2 test used to determine infection status was included in the study. Other factors extracted from the electronic medical record include age, sex, marital status, race/ethnicity, insurance status, cancer type, cancer treatment, and period when the patient tested positive for COVID (February-June, July-September, and October-December 2020). Subjects were linked by their primary address to the US Census Bureau's American Community Survey data, a nationwide survey including demographic, housing and socioeconomic data, and to real estate tax data from New York's Department of City Planning. 7, 8 We abstracted each patient's building-level characteristics, including assessed value (mean), residential units per building, and neighborhood level variables, including unemployment rate, racial and ethnic composition, median household income, percentage of families below the poverty rate, number of occupants per room (household crowding), average household size and membership, highest educational attainment, primary language spoken within the home, and population density of the neighborhood. New York City neighborhood tabulation areas were used to define a neighborhood. 8 We fit unadjusted logistic regression models to estimate odds ratios (ORs) between each neighborhood socioeconomic and environment variable and SARS-CoV-2 infection, accounting for neighborhood clustering as described previously. 9 We fit similar models further adjusting for patient characteristics selected on the basis of their a priori possibility of confounding the association. Analyses were conducted using SAS 9.4 (SAS Institute Inc., Cary, North Carolina). This study was approved by the Columbia University Institutional Review Board. The authors have no conflict of interest in relation to this work.

| RESULTS
We identified 2489 New York City residents with cancer receiving treatment including 2350 (94.4%) that were linked to neighborhoods and buildings in the city. Overall, 214 (9.1%) were infected with SARS-CoV-2 ( Table 1)  were associated with SARS-CoV-2 infection (Supplemental Table).

ACKNOWLEDGMENTS
Dr. Wright has served as a consultant for Clovis Oncology, received royalties from UpToDate, and received research support from Merck.

CONFLICT OF INTEREST
The authors have stated explicitly that there are no conflicts of interest in connection with this article.

DATA AVAILABILITY STATEMENT
The data that support the findings of this study are available on request from the corresponding author. The data are not publicly available due to privacy or ethical restrictions.

ETHICS STATEMENT
Authors confirm that all procedures followed, were in accordance with the ethical standards with the Helsinki declaration of 1975, as revised in 2000.